Jinhyuk Kim

Co-variation of depressive mood and locomotor dynamics evaluated by ecological momentary assessment in healthy humans.

Computerized ecological momentary assessment (EMA) is widely accepted as a “gold standard” method for capturing momentary symptoms repeatedly experienced in daily life. Although many studies have addressed the within-individual temporal variations in momentary symptoms compared with simultaneously measured external criteria, their concurrent associations, specifically with continuous physiological measures, have not been rigorously examined. Therefore, in the present study, we first examined the variations in momentary symptoms by validating the associations among self-reported symptoms measured simultaneously (depressive mood, anxious mood, and fatigue) and then investigated covariant properties between the symptoms (especially, depressive mood) and local statistics of locomotor activity as the external objective criteria obtained continuously. Healthy subjects (N = 85) from three different populations (adolescents, undergraduates, and office workers) wore a watch-type computer device equipped with EMA software for recording the momentary symptoms experienced by the subjects. Locomotor activity data were also continuously obtained by using an actigraph built into the device. Multilevel modeling analysis confirmed convergent associations by showing positive correlations among momentary symptoms. The increased intermittency of locomotor activity, characterized by a combination of reduced activity with occasional bursts, appeared concurrently with the worsening of depressive mood. Further, this association remained statistically unchanged across groups regardless of group differences in age, lifestyle, and occupation. These results indicate that the temporal variations in the momentary symptoms are not random but reflect the underlying changes in psychophysiological variables in daily life. In addition, our findings on the concurrent changes in depressive mood and locomotor activity may contribute to the continuous estimation of changes in depressive mood and early detection of depressive disorders.

Systematic comparison between ecological momentary assessment and day reconstruction method for fatigue and mood states in healthy adults

OBJECTIVES While both ecological momentary assessment (EMA) and the day reconstruction method (DRM) have been used to overcome recall bias, a full systematic comparison of these methods has not been conducted. This study was aimed to investigate the differences and correlations between momentary fatigue and mood states recorded by EMA and reconstructed ones recorded by simultaneous DRM in healthy adults. DESIGN Each of two different designs (time-based and episode-based) of EMA and DRM were simultaneously conducted. METHODS Twenty-five healthy adults recorded momentary fatigue and mood states with EMA, and then, reconstructed them with DRM. Differences between the mean and the variability of momentary and reconstructed recordings, and the correlations between them, are analysed for different EMA designs. RESULTS No significant differences are found between the mean or the variability of EMA and DRM estimated over the monitoring period. However, correlations between EMA and DRM are low, albeit statistically significant. CONCLUSIONS Although the overall mean and variability of EMA recordings may be accessible with DRM, detailed changes over time of momentary fatigue and mood states are not retrieved by DRM. Statement of contribution What is already known on this subject? Day reconstruction method (DRM) may be a reliable substitute strategy for the measurement of subjective symptoms instead of ecological momentary assessment (EMA). Remembering the context of daily activities with DRM is assumed to be helpful in reconstructing subjective symptoms without recall bias. What does this study add? We are not able to reconstruct our diurnal time course (i.e. detailed changes over time) of subjective symptoms (e.g. fatigue and mood states in this study) with DRM, while their approximate mean and overall variability during the study period may be accessible with DRM. Reconstructed depression by DRM could be biased when the subjects remembered whether their behaviour was active or inactive.

Covariation of Depressive Mood and Spontaneous Physical Activity in Major Depressive Disorder: Toward Continuous Monitoring of Depressive Mood

The objective evaluation of depressive mood is considered to be useful for the diagnosis and treatment of depressive disorders. Thus, we investigated psychobehavioral correlates, particularly the statistical associations between momentary depressive mood and behavioral dynamics measured objectively, in patients with major depressive disorder (MDD) and healthy subjects. Patients with MDD (n = 14) and healthy subjects (n = 43) wore a watch-type computer device and rated their momentary symptoms using ecological momentary assessment. Spontaneous physical activity in daily life, referred to as locomotor activity, was also continuously measured by an activity monitor built into the device. A multilevel modeling approach was used to model the associations between changes in depressive mood scores and the local statistics of locomotor activity simultaneously measured. We further examined the cross validity of such associations across groups. The statistical model established indicated that worsening of the depressive mood was associated with the increased intermittency of locomotor activity, as characterized by a lower mean and higher skewness. The model was cross validated across groups, suggesting that the same psychobehavioral correlates are shared by both healthy subjects and patients, although the latter had significantly higher mean levels of depressive mood scores. Our findings suggest the presence of robust as well as common associations between momentary depressive mood and behavioral dynamics in healthy individuals and patients with depression, which may lead to the continuous monitoring of the pathogenic processes (from healthy states) and pathological states of MDD.

Co-variation of depressive mood and spontaneous physical activity evaluated by ecological momentary assessment in major depressive disorder

The objective evaluation of depressive mood is thought to be useful for the diagnosis and treatment of depressive disorders. Thus, we investigated psychobehavioral correlates, particularly the statistical associations between momentary depressive mood and behavioral dynamics measured objectively, in patients with major depressive disorder (MDD). Patients with MDD (n = 14) wore a watch-type computer device and rated their momentary symptoms using ecological momentary assessment. Spontaneous physical activity in daily life, referred to as locomotor activity, was also continuously measured by an activity monitor built into the device. A multilevel modeling approach was used to model the associations between changes in depressive mood scores and the local statistics of locomotor activity simultaneously measured. The statistical model constructed indicated that worsening of depressive mood was associated with increased intermittency of locomotor activity, as characterized by a lower mean and higher skewness. Our findings suggest the presence of associations between momentary depressive mood and behavioral dynamics in patients with depression, which may lead to the continuous monitoring of the pathological states of MDD.

Intermittent locomotor dynamics and its transitions in bipolar disorder

The scale-invariant and intermittent dynamics of human behavior are currently attracting great scientific interest. We have recently reported the universal laws of behavioral organization, especially those describing the complexity of behavioral dynamics, shared by humans and wild-type mice. We also demonstrated the alterations of the law of resting period distributions shared among patients with major depressive disorders, mice with deficiency in a circadian clock gene (Period 2), and patients with schizophrenia. These findings indicate that the statistical laws of behavioral organization provide an objective biobehavioral measures for psychiatric disorders, and the study of behavioral organization could provide further insight into the pathophysiological mechanism. Based on these studies, we recently started ultra long-term continuous recording of locomotor activity and self-reported symptoms for bipolar patients to capture transitions of pathological states (i.e. switching processes between depressive and manic/hypomanic phases), and then succeeded in obtaining a simultaneous recording of dynamical changes in mood and locomotor activity from one patient during a pathological phase transition. To our knowledge, this is the first successful case for such a long-term, high frequency and high resolution recording enabling the study of behavioral dynamics in transitions. In this paper, we show characteristic phenomena in the period preceding the transition from depressive to hypomanic phase, suggestive of the existence of an early warning sign (referred to as critical slowing down) before such a transition. In addition, we demonstrate the significant correlation between mood scores and scaling exponents of resting period distributions. These findings suggest a possibility for quantitative evaluation and/or prediction of pathological states and their transitions in bipolar disorder.

Application of Empirical Mode Decomposition to Mother and Infant Physical Activity

BACKGROUND The mutual dependencies between mother and infant circadian rhythms are important for examining disturbances of maternal circadian rhythms, which are considered substantial risk factors for the development of maternal depression during childrearing periods. OBJECTIVES We characterized the mutual dependencies of maternal-infant circadian rhythms by an index of synchronization properties and then tested the hypothesis that such an index, specifically the instantaneous phase differences between their rhythms, is associated with maternal mental health. METHODS We performed longitudinal recordings of maternal symptoms of fatigue, stress, and mood states by ecological momentary assessment, together with simultaneous measurements of mother and infant physical activity data in daily life, on 20 mother-infant pairs for a period of >1 week. The circadian components in their physical activity data were extracted by ensembled bivariate empirical mode decomposition, and the corresponding instantaneous phases were then obtained based on the Hilbert transformation. The associations between diurnal maternal symptoms and absolute phase differences between mother and infant circadian rhythms were tested by multilevel models. RESULTS Diurnal fatigue and depressive mood scores showed positive and significant correlations (p < 0.05) with the increase in instantaneous mother-infant phase differences, indicating the significant role of synchronization of mother-infant circadian rhythms for maintaining maternal mental health. CONCLUSIONS These findings suggest that modifications of maternal and/or infant circadian rhythms may lead to the improvement of maternal mental health during child-rearing periods.

A momentary biomarker for depressive mood

Many biomarkers from genetic, neuroimaging, and biological/biochemical measures have been recently developed in order to make a shift toward the objective evaluation of psychiatric disorders. However, they have so far been less successful in capturing dynamical changes or transitions in pathological states, such as those occurring during the course of clinical treatments or pathogenic processes of disorders. A momentary biomarker is now required for objective monitoring of such dynamical changes. The development of ecological momentary assessment (EMA) allows the assessment of dynamical aspects of diurnal/daily clinical conditions and subjective symptoms. Furthermore, a variety of validation studies on momentary symptoms assessed by EMA using behavioral/physiological/biochemical measures have demonstrated the possibility of evaluating momentary symptoms from such external objective measures. In this review, we introduce physical activity as a candidate biobehavioral biomarker for psychiatric disorders. We also mention its potential as a momentary biomarker for depressive mood. Finally, we address the continuous monitoring of the pathogenic processes and pathological states of depressive disorders based on physical activity, as well as its application in pharmacological animal studies.

Acoustic Hyper-Reactivity and Negatively Skewed Locomotor Activity in Children With Autism Spectrum Disorders: An Exploratory Study

Investigation of objective and quantitative behavioral phenotypes along with neurobiological endophenotypes might lead to increased knowledge of the mechanisms that underlie autism spectrum disorders (ASD). Here, we investigated the association between locomotor dynamics and characteristics of the acoustic startle response (ASR) and its modulation in ASD (n = 14) and typically developing (TD, n = 13) children. The ASR was recorded in response to acoustic stimuli in increments of 10 dB (65–105 dB SPL). We calculated the average ASR magnitude for each stimulus intensity and peak-ASR latency. Locomotor activity was continuously measured with a watch-type actigraph. We examined statistics of locomotor activity, such as mean activity levels and the skewness of activity. Children with ASD had a significantly greater ASR magnitude in response to a weak acoustic stimulus, which reflects acoustic hyper-reactivity. The skewness of all-day activity was significantly more negative in children with ASD than those with TD. Skewness of daytime activity was also more negative, although only of borderline statistical significance. For all children, the higher mean and more negatively skewed daytime activity, reflecting hyperactivity that was associated with sporadic large daytime “troughs,” was significantly correlated with acoustic hyper-reactivity. The more negatively skewed locomotor activity occurring in the daytime was also associated with impaired sensorimotor gating, examined as prepulse inhibition at a prepulse intensity of 70 dB. This comprehensive investigation of locomotor dynamics and the ASR extends our understanding of the neurophysiology that underlies ASD.

Towards Continuous Monitoring of Depressive Mood from Locomotor Activity in Major Depressive Disorder

In this study, we measured self-reported depressive mood using Ecological Momentary Assessment and locomotor activity simultaneously in healthy subjects (n=43) and patients with major depressive disorder (MDD; n=14). Multilevel modeling approach showed significant associations of changes between depressive mood scores and intermittency of local locomotor activity, reflecting situations in which the depressive mood becomes worse with both lower activity levels and more frequent episodes of bursts of locomotor activity. Further, the personalized optimization method enhanced the prediction accuracy of the constructed model in MDD patients. These results suggest the possibility for continuous monitoring of depressive mood based on locomotor activity.